Drawing upon the Search for Ideas in Associative Memory (SIAM) model as the theoretical framework, the impact of heterogeneity and topic relevance of visual stimuli on ideation performance was examined. Results from a laboratory experiment showed that visual stimuli increased productivity and diversity of idea generation, that relevance to the…

Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…